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Two-Stage Neural Network Approach to Precise 24-Hour Load Pattern Prediction

  • Krzysztof Siwek
  • Stanislaw Osowski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5572)

Abstract

The paper presents the neural network approach to the precise 24-hour load pattern prediction for the next day in the power system. In this approach we use the ensemble of few neural network predictors working in parallel. The predicted series containing 24 values of the load pattern generated by the neural predictors are combined together using principal component analysis. Few principal components form the input vector for the final stage predictor composed of another neural network. The developed system of prediction was tested on the real data of the Polish Power System. The results have been compared to the appropriate values generated by other methods.

Keywords

load forecasting neural networks PCA 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Krzysztof Siwek
    • 1
  • Stanislaw Osowski
    • 1
    • 2
  1. 1.Dept. of Electrical EngineeringWarsaw University of TechnologyWarsawPoland
  2. 2.Dept. of ElectronicsMilitary University of TechnologyWarsawPoland

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